基于EMD与SVD的齿轮箱分形诊断方法研究

提出了一种基于经验模态分解(EMD)与奇异值分解(SVD)的机械振动系统故障分形诊断方法。该方法首先将EMD和SVD相结合,对信号进行分解和特征筛选,通过重组所得轨道矩阵,实现对机械系统振动信号不同特征信息的提取。然后利用Kolmogorov熵、多重分形等动力学分析方法,对降噪振动信号进行分形诊断。在直齿轮减速箱故障识别中的应用表明,该方法不仅有效提取出了系统的特征信息,而且可实现对系统状态和细微故障差别的有效识别,并可给出定量判据。

Research of fractal diagnosis method for gearbox based on EMD and SVD

A fractal diagnosis method for the mechanical vibration system based on empirical mode decomposition （EMD） and singular value decomposition （SVD） is proposed. Firstly, with EMD and SVD, the signal is decomposed. The orbit matrix can be obtained through characteristic selection. And the different diagnostic information of the vibration sig- nal can be extracted with the orbit matrix recombination. Then the denoising signal can be analyzed by the dynamistic analysis methods, such as Kolmogorov entropy, multi-fractal, and so on. The application to the failure recognition of the spur gearbox shows that the method not only effectively extracts the characteristics of the system, but also achieves the effective recognition of the system state. And the quantitative criterion can be presented. It can provide the difference identification of imperceptible fault for the system.